Chain Rule & Partial Derivative Proofs: Understand Easily!

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In summary: It may also be helpful to consult other sources for alternative explanations and perspectives. Good luck!In summary, the conversation is about finding a good resource for understanding the multivariable chain rule and partial derivative proof. The expert provides a summary of the concepts, explaining the equations and notation used in the proof. They also suggest looking at an informal demonstration and consulting other sources for a better understanding.
  • #1
Petrus
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Hello MHB,
anyone know good Link with good explaining on multivariable chain rule and partial derivate proof?I am having hard to understand the proof.
Regards,
\(\displaystyle |\pi\rangle\)
 
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  • #2
Petrus said:
Hello MHB,
anyone know good Link with good explaining on multivariable chain rule and partial derivate proof?I am having hard to understand the proof.
Regards,
\(\displaystyle |\pi\rangle\)

Hi $|Petrus\rangle$,

Well, googling for it, http://www.math.hmc.edu/calculus/tutorials/multichainrule/ seems to be as good as any.Let me have a go at it to try to explain it.

Suppose we have a function $f(x,y)$.
And suppose both $x$ and $y$ are actually functions of $t$.
So we have $g(t)=f\big(x(t), y(t)\big)$.

Then the multivariable chain rule says that:
$$g'(t) = \frac d{dt}f\big(x(t), y(t)\big) = \frac{\partial}{\partial x}f\big(x(t), y(t)\big) \cdot \frac {d}{dt}x(t) + \frac{\partial}{\partial y}f\big(x(t), y(t)\big) \cdot \frac {d}{dt}y(t)$$
Or for short:
$$g'(t)=\frac {df}{dt} = \frac{\partial f}{\partial x} \cdot \frac {dx}{dt} + \frac{\partial f}{\partial y}\cdot \frac {dy}{dt}$$
 
  • #3
Hello I like Serena,
There is a another way i am suposed to learn I think, I am Really confused.. I know this pic is on Swedish but this is what I am suposed to understand
30serts.jpg


Regards,
\(\displaystyle |\pi\rangle\)
 
  • #4
Well, that first formula is the same as the first formula that I just gave you.
It's just with different symbols and a different notation.

In your slide they use $f_x'\big(g(t), h(t)\big)$ where I was using \(\displaystyle \frac{\partial}{\partial x}f\big(x(t), y(t)\big)\). They mean the same thing.
 
  • #5
I like Serena said:
Well, that first formula is the same as the first formula that I just gave you.
It's just with different symbols and a different notation.

In your slide they use $f_x'\big(g(t), h(t)\big)$ where I was using \(\displaystyle \frac{\partial}{\partial x}f\big(x(t), y(t)\big)\). They mean the same thing.
Hmm I start to confuse myself right now.. Well I am done for today and hopefully evrything start to make sense tomorow! Thanks for taking your time I like Serena!:) (I Will probably be Back tomorow, I just need to take some time with this..)
\(\displaystyle |\pi\rangle\)
 
  • #6
To understand the proof of the multivariable chain rule, I think you will find it helpful to look first at an informal, nonrigorous demonstration, as given http://math.ucsd.edu/~wgarner/reference/math10c_su10/lectures/chain_rule.pdf (you need only look at the first page of that document). That demonstration uses the fact that if $z = f(x,y)$, and the variables $x, y$ are altered by small amounts $\Delta x,\,\Delta y$, then the corresponding change in $z$ is given by the approximate formula $\Delta z \approx \frac{\partial z}{\partial x}\Delta x + \frac{\partial z}{\partial y}\Delta y$. What the Swedish proof does is to take that informal approach and make it rigorous, replacing the approximate formula by an exact formula of the form $\Delta z = \frac{\partial z}{\partial x}\Delta x + \frac{\partial z}{\partial y}\Delta y + E(\Delta x, \Delta y)$. In that formula, the error term $E(\Delta x, \Delta y)$ represents the amount needed to convert the approximate formula into an exact equation. The essential fact about $E(\Delta x, \Delta y)$ is that it is small compared with $\Delta x$ and $\Delta y$. This is expressed by writing $E(\Delta x, \Delta y)$ as $E(\Delta x, \Delta y) = \rho(\Delta x, \Delta y)\sqrt{\Delta x^2 + \Delta y^2},$ where $\rho(\Delta x, \Delta y)$ is a function that tends to $0$ as $(\Delta x, \Delta y) \to (0,0).$

To sum up, make sure that you understand the ideas in the nonrigorous argument first, then go back to the rigorous approach and see what you can make of it.
 

FAQ: Chain Rule & Partial Derivative Proofs: Understand Easily!

What is the chain rule?

The chain rule is a mathematical concept that allows us to calculate the derivative of a composite function. It is used when a function is composed of two or more functions, and we want to find the derivative of the entire function.

Why is the chain rule important?

The chain rule is important because it helps us to find the derivative of complex functions, which are composed of simpler functions. Without the chain rule, we would have to use other methods, which can be more time-consuming and complicated.

What is a partial derivative?

A partial derivative is a derivative of a function with respect to one of its variables, while holding all other variables constant. It is used in multivariable calculus to find the rate of change of a function in a specific direction.

How is the chain rule applied in partial derivatives?

In partial derivatives, the chain rule is used when a function is composed of two or more functions, and we want to find the partial derivative with respect to one of the variables. We apply the chain rule by taking the derivative of the outer function, and then multiplying it by the derivative of the inner function with respect to the variable of interest.

Are there any common mistakes when using the chain rule and partial derivatives?

Yes, some common mistakes when using the chain rule and partial derivatives include forgetting to apply the chain rule, mixing up the order of differentiation, and not setting the other variables to their constant values. It is important to carefully apply the chain rule and double check the calculations to avoid these mistakes.

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